The present invention generally relates to computer analytics, and more specifically to computer analytics as applied to border detection in an image.
Malignant melanoma is one of the most common and the deadliest type of skin cancer. It has been shown that early detection of melanoma and immediate surgical excision of the lesion can increase the survival rate by five folds. Dermoscopy is an important non-invasive tool for clinical diagnosis of melanoma. However, due to subjectivity of human expert in interpretation of skin lesions, computer-based analysis of dermoscopy images has become more popular in the last decade. Skin lesion border detection is the first and a very crucial step towards automated dermoscopy image analysis.
The problem of border detection is not a trivial task. It is indeed an active research area, and a lot of effort has been made to improve lesion segmentation algorithms, including using iterative thresholding, fuzzy logic based thresholding, fusion of thresholds, saliency based border detection, neural network, and supervised learning methods.